Novel Multi-Parametric Sensor System for Comprehensive Multi-Wavelength Photoplethysmography Characterization

Sensors (Basel). 2023 Jul 24;23(14):6628. doi: 10.3390/s23146628.

Abstract

Photoplethysmography (PPG) is widely used to assess cardiovascular health. However, its usage and standardization are limited by the impact of variable contact force and temperature, which influence the accuracy and reliability of the measurements. Although some studies have evaluated the impact of these phenomena on signal amplitude, there is still a lack of knowledge about how these perturbations can distort the signal morphology, especially for multi-wavelength PPG (MW-PPG) measurements. This work presents a modular multi-parametric sensor system that integrates continuous and real-time acquisition of MW-PPG, contact force, and temperature signals. The implemented design solution allows for a comprehensive characterization of the effects of the variations in these phenomena on the contour of the MW-PPG signal. Furthermore, a dynamic DC cancellation circuitry was implemented to improve measurement resolution and obtain high-quality raw multi-parametric data. The accuracy of the MW-PPG signal acquisition was assessed using a synthesized reference PPG optical signal. The performance of the contact force and temperature sensors was evaluated as well. To determine the overall quality of the multi-parametric measurement, an in vivo measurement on the index finger of a volunteer was performed. The results indicate a high precision and accuracy in the measurements, wherein the capacity of the system to obtain high-resolution and low-distortion MW-PPG signals is highlighted. These findings will contribute to developing new signal-processing approaches, advancing the accuracy and robustness of PPG-based systems, and bridging existing gaps in the literature.

Keywords: MW-PPG; PSoC; contact force; multi-wavelength; photoplethysmography; temperature.

MeSH terms

  • Fingers
  • Heart Rate
  • Humans
  • Photoplethysmography* / methods
  • Reproducibility of Results
  • Signal Processing, Computer-Assisted*
  • Volunteers

Grants and funding

This work has been made possible thanks to the Belgian Development Cooperation through VLIR-UOS (Flemish Interuniversity Council-University Cooperation for Development) in the context of the Institutional University Cooperation program (IUC 2019 Phase 2 UO) with the Universidad de Oriente (Cuba). This work has been partially supported by the FWO-Flanders FWOSB106 Ph.D. grant and partially by Innoviris-Brussels through the ILSF project BRGEOZ403.